In computational studies of reaction mechanisms, a prominent methodology known as "transition path sampling" relies on the use of stochastic actions in order to sample the relevant mechanisms. Such actions are determined by the nature of the system under consideration (for example, the specific protein model), and once specified uniquely determine the mechanisms in question. However, in the literature one finds at least two different actions to describe the same given system, and no consensus seems to exist as to which action should be adopted in a given application. [unreadable] [unreadable] In this project, we have attacked and resolved this ambiguity by clarifying the scope and limitations of these two actions, illustrating our findings with simple models of unimolecular reactions. A particularly comforting message is that the computational cost of simulating reaction mechanisms is not as expensive as previously suggested.[unreadable] [unreadable] Aside from the aforementioned ambiguity, we have also investigated the possibility of using stochastic actions to characterize "dominant pathways" in studies of protein folding. Contrary to what has been suggested by others, we have found that methods based on minimization of these actions in general do not yield results of quantitative value. Such findings should aid and guide further progress in the characterization of reaction mechanisms in general.